Workforce

How Human-Machine Partnerships Are Transforming the Workplace: Part 1 (AI and Automation)

Tim Wright By Tim Wright Consultant, Workforce Transformation, Dell Technologies Education Services April 20, 2020

Artificial Intelligence (AI) is now deployed in business of all sizes, and in consumer and residential applications. We project that in the short-term AI applications will experience:

  • Increased spending on design, development and deployment
  • Increased revenue from innovations and application
  • Increased incentive to find innovation in industries, science, and consumer lifestyles

While we see few barriers to the advance of AI, one factor may impede successful AI applications: humans. Employees’ lack of skills and/or comfort working in a human-machine partnership presents a potential and significant obstacle.

Part 1 of this 2-part series examines the current and future transition to AI and automation, and the impact on work and the workforce. Part 2 explores both workers’ and companies’ reactions to AI changes and changes to the workforce.

The Transition to AI

In 2017 the Institute for the Future, in concert with Dell Technologies, reported that approximately 1,500 North American companies were “doing something related to AI”. That was less than 1% of all medium-to-large companies.

Two years later, Gartner’s global survey of 3,000 CIOs from 89 countries, returned data that 37% of their companies utilized some form of AI. That is not to suggest 2 years’ growth of 3600%; the survey of CIOs explored larger companies with proportionately larger budgets and the greater likelihood of technological innovations such as AI.

Still, those and similar surveys share IT executives’ and professionals’ predictions of significant increase in AI deployment through 2030. Technological advances regarding Big Data and Data Science, and an open field to roll out AI innovations, make it no surprise that almost 90% of 1,500 IT professionals responding to Cognilytica’s survey expect to see implementation of AI underway before 2022. Similarly, in December 2019, Gartner asked about the immediate future in the survey of IT and IT/business professionals who were “required to be knowledgeable about the business and technology aspects of ML or AI.” They forecast a rapid acceleration of AI adoption (Figure 1):

Figure 1: Average Number of AI or ML Projects Deployed (Mean). Source: Gartner AI and ML Development Strategies Survey

The Impact of AI on Work and the Workforce

AI puts Machine Learning and analysis of Big Data to work in areas such as:

  • Manufacturing efficiency and productivity
  • Marketing and sales-explicit targeting
  • Product design and usability

AI performs functions from completing forms, graphs, and reports predicting customers’ buying habits to simulating automobile design, developing pharmaceuticals, and producing entertainment. Applications will increase in number, variety, and complexity.

Complementing their 2017 report with 2018-19 research, McKinsey & Company finds that

Automation will have a lesser effect on jobs that involve managing people, applying expertise, and social interactions, where machines are unable to match human performance for now.

Still, as AI technology advances, the impact on the work humans perform increases.

Jobs are comprised of tasks. Almost half of the 1,200 executives surveyed by Accenture in 2018 say that traditional jobs are becoming obsolete because AI assumes the repetitive tasks in process-based work. Redesign of jobs by 29% of those executives’ companies meant recombining tasks to maximize the value of the human-machine partnerships. Consequently, 63% of the respondents believe that AI will increase the number of jobs in their organizations within 3 years (by 2021).

This realignment of human skills and machine functions directly impacts the nature of the work, changing the skills and attitudes expected of workers.

AI will impact the workforce in two distinct ways:

  • An increased requirement for advanced technological skills: high-end programming, data mining, data analytics, and data translation
  • Skills beyond the reach of AI becoming more critical for humans to possess: creative thinking, imagination, multi-level decision-making, design, strategy, and communication

The increasing need for both technical and cognitive skills is why IDC predicts that by 2025 75% of organizations adopting AI will be investing in these areas of employee training. Jeff Wong, Global Chief Innovation Officer with EY, sees AI shifting the nature of jobs.

As businesses deploy AI strategies, they’re increasingly aware of how the roles, responsibilities and skills of their talent [are] changing. With AI taking a leading role on tackling organizations’ simple and repetitive tasks, the human workforce can focus more on complex work that ultimately provides a greater level of professional fulfillment to employees and a more efficient use of critical thinking power.

Figure 2: EMTech Digital Conference survey respondents’ view of AI’s impact on jobs. Source: MIT Technology Review.

In traditional companies, an individual’s skill set has been a blend of various technical, quantitative, and interpersonal skills. The successful employee applied those skills in the right configuration to fit the immediate situation. The introduction of AI into a workplace will bring more discrete attention to these skill categories:

  • Process-oriented skills apply to filing, manufacturing, and following processes
  • Quantitative-reasoning skills utilize advanced mathematics to interpret analytics and to make recommendations, decisions. adjustments
  • Social-ability and creativity skills cover the full range of communication, persuasion, conflict resolution, critical and strategic thinking, complex information processing, and interpersonal relations

Process-oriented skills directly serve the functions fulfilled by AI. Quantitative reasoning is relevant to AI to a degree that will increase as AI technologies advance. Social-ability skills will remain predominantly human-performed in even the most AI-enhanced organizations. Pedro Uria-Recio predicts that this decade, 2020-29, will see those skills broken down in this way:

  • 80% of the process-oriented tasks performed by AI
  • 50% of the quantitative-reasoning tasks by humans, 50% by AI
  • 80% of the social-ability skills performed by humans

IDC predicts that by 2025, 75% of organizations adopting AI will be investing in employee training to fill skills gaps caused by adoption of AI.

Summary: Action Items for Planning

The overall changes brought about by the transition to AI across all industries and the impacts already felt among companies’ workforces demonstrate that plans are essential to accommodate the technological transformation. Planning must include attention to changes that impact the workforce, and ensure those changes are not merely acceptable, but actually favorable to those most affected. The workforce is most affected, immediately, by transition to AI and automation.

Here are two action items to include in your planning:

  • Project the degree and rate that AI will increase within your company
  • Identify the specific changes AI will generate by changing the assignment of tasks: machine tasks as opposed to cognitive tasks

Part 2 of How Human-Machine Partnerships Are Transforming the Workplace will look closely at the reactions of workers to the workforce transformation we’ve detailed here. That article will examine conceptual considerations as well as recommended actions for companies to consider to maximize integration of their technological and workforce transformations.

How is AI being applied and enabled at the enterprise level within your organization?

Tim Wright

About Tim Wright


Consultant, Workforce Transformation, Dell Technologies Education Services

Tim Wright joined Dell EMC, now Dell Technologies, in 2013 as Consultant-Professional Development in the then GSD L&D organization. His focus initially was on providing professional/personal skills improvement resources for members of the training delivery organization. That soon expanded to Tim’s development of a series of virtual instructor-led professional development courses that ran successfully for the SDS organization.

After teaching middle school for 13 years—to individuals now in their late 40s and early 50s!—Tim navigated to corporate training and development. He’s been at it as the industry’s changed its name from “corporate training” to “training and development” to “corporate learning” to “L&D” to “digital learning”….. His focus has always been in the area of interpersonal skills: professional development, soft skills, generic training. Whether communication skills or team building or leadership development or problem-solving and decision-making, Tim’s passion is helping people discover ways to improve their performance while increasing enjoyment of what they do.

As much as possible, Tim enjoys a 40-40-20 approach to his work. Ideally, he spends 40% of his time interacting with stakeholders to engage in the observation-interview-empathize segments of Design Thinking. The next 40% continues DT practices of prototyping, sharing with stakeholders, testing. The last 20% is the delivery or iteration where failure is discovered as the fastest step to improvement. He even envisions a project that allows him to fit that formula into a 5 day week: M-T is design, W-T is development, F is delivery.

Tim’s pretty much given up running for long-distance walking/hiking. His golf game is improving. He journals like crazy and is always working on another poem.

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